Pathways for Healthcare Organizations to Strengthen Indigenous Nurse Retention
Bibliographic record
Abstract
Call to Action #92 encourages corporations to apply the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) as an organizational framework and provides concrete strategies to guide policy and operational activities to increase Indigenous participation in the economy (Truth and Reconciliation Commission of Canada 2015b; UN 2007).Call to Action #92 and the UNDRIP are explored to provide strategies to decolonize mainstream healthcare organizations and promote workplace structures that assist Indigenous nurses in thriving in the work setting.The recommendations in this synthesis paper can be used by healthcare organizations to support Indigenous reconciliation in Canada. Pathways for Healthcare Organizations to Strengthen Indigenous Nurse RetentionThe Truth and Reconciliation Commission of Canada (2015a) outlines pathways to support Indigenous 1 health and equity through 94 calls to action, asserting that all Canadians have a responsibility to enact the recommendations."Call to Action #92" is the focus of this discussion as it outlines how institutions, such as those that make up the health system, can support Indigenous Peoples as full participants in the economy.Call to Action #92 encourages corporations to apply
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.003 | 0.026 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.038 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".